The world of search is changing. As technical SEO specialists, we’ve always paid attention to algorithm updates and user behavior, but today the landscape is being reshaped by something much bigger: AI-driven chatbots.
Tools like OpenAI’s ChatGPT, Anthropic’s Claude, Google’s AI Overviews, and new players like Perplexity are redefining how users find information. And for brands this means a new frontier: earning visibility inside AI generated responses.
From Traditional Search to AI Conversations
Generative AI isn’t just enhancing the search experience—it’s changing it. A recent Bain & Company study found that 80% of users now use AI-generated results for at least 40% of their searches, with nearly 60% of those searches ending without a website click.
This is already eating into organic traffic and click-through rates. But more importantly, it’s forcing us to rethink how SEO works in this new world, as you can see on this website.
Traditional tactics of indexing, backlinks, and structured data are still important, but we now also need to consider how AI models interpret content, context, and authority.
How Chatbots Evaluate Content?
Unlike traditional search engines, AI chatbots don’t just crawl the web. They blend multiple layers of logic:
- Credibility and authority signals
- Sentiment analysis
- Relevance to conversational queries
- Consistency of facts and tone
For example, ChatGPT layers traditional search with model-based reasoning to offer what it calls “thoughtful answers”. A basic keyword match no longer cuts it. We must now optimise for context.
Measuring AI Visibility: Tools and Tactics
Just as we used to measure keyword rankings on Google, we’re now seeing a wave of tools to measure brand visibility within AI responses.
- Brandtech’s “Share of Model” tool tracks how often brands appear across major LLMs.
- Profound analyses of sentiment and visibility across thousands of industry prompts.
- Deep, backed by Khosla Ventures, provides detailed reporting on brand mentions across AI-powered tools. These platforms input thousands of prompts into chatbots, record the outputs, and score brand presence. This gives us insight into how often—and how favourably—brands are mentioned in AI-generated answers.
Tech SEO for an AI-First World
We need to go beyond traditional SEO frameworks. Here’s how we’re evolving our technical SEO strategy for the age of chatbots:
1. Structured Data Still Matters
Schema markup gives AI models the context they need. We wrap all key content in structured data, especially for products, how-to guides, FAQs, and videos.
2. Content Hubs Build Authority
Topic clusters are key. AI models prefer consistent signals from domain experts. We structure our sites around focused content hubs that demonstrate ongoing thought leadership.
3. Optimize for Conversational Prompts
Searches are becoming more detailed and human-like. We write content around natural language phrases like “best kid-friendly restaurants with outdoor seating in San Diego.”
4. Boost On-Page Credibility Signals
Models judge credibility in real time. We add author bios, cite sources, display last updated dates, and ensure transparency in all claims.
5. Content Quality Over Quantity
Keyword stuffing is dead. AI models reward relevance, factual integrity, and semantic depth. We prioritise clarity, accuracy, and usefulness.
Agencies are Evolving or Being Replaced
The AI wave is also disrupting traditional ad agencies. Platforms like Meta and Google are pushing self-serve AI ad tools, allowing brands to run campaigns autonomously.
But forward-thinking agencies are pivoting. Many are now offering AI visibility optimisation, helping brands restructure their web presence to surface more often in tools like ChatGPT and Claude.
As Jack Smyth of Brandtech said, “Large language models are the ultimate influencer.”
Global Adoption is Accelerating
Companies like Ramp, Indeed and Chivas Brothers are early adopters of these new AI visibility tools. And in markets like India AI integration is surging. According to IBM 59% of large Indian enterprises are already using AI in their operations, with 74% increasing their AI budgets in areas like R&D and SEO.
The New Challenges of AI SEO
As great as AI search is, it presents new challenges:
- Opaque algorithms: AI models don’t offer the transparency we’re used to from traditional search engines.
- Skill gaps: We need talent that understands LLM behavior, prompt engineering, and AI ethics.
- Higher content standards: LLMs are getting better at spotting thin, misleading, or irrelevant content.
According to Adam Fry, Search Lead at ChatGPT, users are moving from generic keywords to high-context questions, such as:
“Can you recommend a quiet restaurant for a family of five near Central Park?”
These types of prompts require content that’s not just keyword optimised, but detailed, nuanced, and intent-matching.
Enter: AI Native Advertising
We’re also watching platforms like Perplexity, which are testing sponsored questions—a new form of native advertising inside AI tools. This is a growing opportunity for brands to get embedded in AI conversations.
But as Denis Yarats, co-founder of Perplexity, says:
“It’s much harder to be an SEO target in this world. The only real strategy is to be as relevant and valuable as possible.”
Final Take: Adapt or Die
We think this is SEO’s CD-to-Spotify moment. Traditional search has dominated for decades, but generative AI is breaking that monopoly.
As technical SEO specialists, we know that:
- Structured data still matters—but context is everything
- Ranking in AI means being credible, consistent, and human
- Optimisation now means influencing language models, not just algorithms
In a world mediated by intelligent systems, we can’t game our way to the top anymore. We must earn our spot with useful content.